Search Results (4,660)

To investigate the characteristics of rhizosphere soil microbial communities associated with Schisandra sphenanthera across different altitudinal gradients and to reveal the driving factors of microbial community dynamics, this study collected rhizosphere soil samples at four elevations: 900 m (HB1), 1100 m (HB2), 1300 m (HB3), and 1500 m (HB4). High-throughput sequencing and molecular ecological network analysis were employed to analyze the microbial community composition and species interactions. A null model was applied to elucidate community assembly mechanisms. The results demonstrated that bacterial communities were dominated by Proteobacteria, Acidobacteriota, Actinobacteriota, and Chloroflexi. The relative abundance of Proteobacteria increased with elevation, while that of Acidobacteriota and Actinobacteriota declined. Fungal communities were primarily composed of Ascomycota and Basidiomycota, with both showing elevated relative abundances at higher altitudes. Diversity indices revealed that HB2 exhibited the highest bacterial Chao, Ace, and Shannon indices but the lowest Simpson index. For fungi, HB3 displayed the highest Chao and Ace indices, whereas HB4 showed the highest Shannon index and the lowest Simpson index. Ecological network analysis indicated stronger bacterial competition at lower elevations and enhanced cooperation at higher elevations, contrasting with fungal communities that exhibited increased competition at higher altitudes. Altitude and soil nutrients were negatively correlated with soil carbon content, while plant nutrients and fungal diversity positively correlated with soil carbon. Null model analysis suggested that deterministic processes dominated bacterial community assembly, whereas stochastic processes governed fungal assembly. These findings highlight significant altitudinal shifts in the microbial community structure and assembly mechanisms in S. sphenanthera rhizosphere soils, driven by the synergistic effects of soil nutrients, plant growth, and fungal diversity. This study provides critical insights into microbial ecology and carbon cycling in alpine ecosystems, offering a scientific basis for ecosystem management and conservation. Full article

Recombinant protein hydrogels have emerged as transformative biomaterials that overcome the bioinertness and unpredictable degradation of traditional synthetic systems by leveraging genetically engineered backbones, such as elastin-like polypeptides, SF, and resilin-like polypeptides, to replicate extracellular matrix (ECM) dynamics and enable programmable functionality. Constructed through a hierarchical crosslinking strategy, these hydrogels integrate reversible physical interactions with covalent crosslinking approaches, collectively endowing the system with mechanical strength, environmental responsiveness, and controlled degradation behavior. Critically, molecular engineering strategies serve as the cornerstone for functional precision: domain-directed self-assembly exploits coiled-coil or β-sheet motifs to orchestrate hierarchical organization, while modular fusion of bioactive motifs through genetic encoding or site-specific conjugation enables dynamic control over cellular interactions and therapeutic release. Such engineered designs underpin advanced applications, including immunomodulatory scaffolds for diabetic wound regeneration, tumor-microenvironment-responsive drug depots, and shear-thinning bioinks for vascularized bioprinting, by synergizing material properties with biological cues. By uniting synthetic biology with materials science, recombinant hydrogels deliver unprecedented flexibility in tuning physical and biological properties. This review synthesizes emerging crosslinking paradigms and molecular strategies, offering a framework for engineering next-generation, adaptive biomaterials poised to address complex challenges in regenerative medicine and beyond. Full article

In this study, growth mechanisms are proposed to understand how banded dendritic crystal aggregates in poly(1,4-butylene adipate) (PBA) transform into straight dendrites upon dilution with a large quantity of poly(ethylene oxide) (PEO) (25–90 wt.%). In growth packing, crystal plates are deformed in numerous ways, such as bending, scrolling, and twisting in self-assembly, into final aggregated morphologies of periodic bands or straight dendrites. Diluting PBA with a significant amount of PEO uncovers intricate periodic banded assemblies, facilitating better structural analysis. Both circularly banded and straight dendritic PBA aggregates have similar basic lamellar patterns. In straight dendritic PBA spherulites, crystal plates can twist from edge-on to flat-on, similar to those in ring-banded spherulites. Therefore, twists—whether continuous or discontinuous—are not limited to the conventional models proposed for classical periodic-banded spherulites. Thus, it would not be universally accurate to claim that the periodic circular bands observed in polymers or small-molecule compounds are caused by continuous lamellar helix twists. Straight dendrites, which do not exhibit optical bands, may also involve alternate crystal twists or scrolls during growth. Iridescence tests are used to compare the differences in crystal assemblies of straight dendrites vs. circularly banded PBA crystals. Full article

Pilot production is a critical transitional phase in the process of new product development or manufacturing, aiming at ensuring that products are thoroughly validated and optimized before entering full-scale production. During this stage, a key challenge is how to leverage limited resources to build data infrastructure and conduct data analysis to establish and verify quality control. This paper presents the implementation of a cyber–physical system (CPS) for a lithium battery pilot assembly line. A machine learning-based predictive model was employed to establish quality control mechanisms. Process knowledge-guided data analysis was utilized to build a quality prediction model based on the collected battery data. The model-centric concept of ‘virtual quality’ enables early quality judgment during production, which allows for flexible quality control and the determination of optimal process parameters, thereby reducing production costs and minimizing energy consumption during manufacturing. Full article

This study focuses on the optimization of valve assemblies in downhole rod pumping units (DRPUs), which remain the predominant artificial lift technology in oil production worldwide. The research addresses the critical issue of premature failures in DRPUs caused by leakage in valve pairs, i.e., a problem that accounts for approximately 15% of all failures, as identified in a statistical analysis of the 2022 operational data from the Uzen oilfield in Kazakhstan. The leakage is primarily attributed to the accumulation of mechanical impurities and paraffin deposits between the valve ball and seat, leading to concentrated surface wear and compromised sealing. To mitigate this issue, a novel valve assembly design was developed featuring a flow turbulizer positioned beneath the valve seat. The turbulizer generates controlled vortex motion in the fluid flow, which increases the rotational frequency of the valve ball during operation. This motion promotes more uniform wear across the contact surfaces and reduces the risk of localized degradation. The turbulizers were manufactured using additive FDM technology, and several design variants were tested in a full-scale laboratory setup simulating downhole conditions. Experimental results revealed that the most effective configuration was a spiral plate turbulizer with a 7.5 mm width, installed without axis deviation from the vertical, which achieved the highest ball rotation frequency and enhanced lapping effect between the ball and the seat. Subsequent field trials using valves with duralumin-based turbulizers demonstrated increased operational lifespans compared to standard valves, confirming the viability of the proposed solution. However, cases of abrasive wear were observed under conditions of high mechanical impurity concentration, indicating the need for more durable materials. To address this, the study recommends transitioning to 316 L stainless steel for turbulizer fabrication due to its superior tensile strength, corrosion resistance, and wear resistance. Implementing this design improvement can significantly reduce maintenance intervals, improve pump reliability, and lower operating costs in mature oilfields with high water cut and solid content. The findings of this research contribute to the broader efforts in petroleum engineering to enhance the longevity and performance of artificial lift systems through targeted mechanical design improvements and material innovation. Full article

Heat stress (HS) is a major environmental factor negatively impacting the reproductive performance of livestock. This study investigates the molecular mechanisms of heat stress on the hypothalamic–pituitary–ovarian (HPO) axis in Hu sheep. A heat-stressed animal model was established, and high-throughput RNA sequencing (RNA-seq) was employed to analyze gene expression in the hypothalamus, pituitary, and ovarian tissues of both control and heat-stressed groups. The results revealed significant changes in estrus behavior, hormone secretion, and reproductive health in heat-stressed sheep, with a shortened estrus duration, prolonged estrous cycles, and decreased levels of FSH, LH, E₂, and P4. A total of 520, 649, and 482 differentially expressed genes (DEGs) were identified in the hypothalamus, pituitary, and ovary, respectively. The DEGs were enriched in pathways related to hormone secretion, neurotransmission, cell proliferation, and immune response, with significant involvement of the p53 and cAMP signaling pathways. Tissue-specific responses to heat stress were observed, with distinct regulatory roles in each organ, including GPCR activity and cytokine signaling in the hypothalamus, calcium-regulated exocytosis in the pituitary, and cilium assembly and ATP binding in the ovary. Key genes such as SYN3, RPH3A, and IGFBP2 were identified as central to the coordinated regulation of the HPO axis. These findings provide new insights into the molecular basis of heat stress-induced impairments in reproductive function—manifested by altered estrous behavior, reduced hormone secretion (FSH, LH, E₂, and P4), and disrupted gene expression in the hypothalamic–pituitary–ovarian (HPO) axis—and offer potential targets for improving heat tolerance and reproductive regulation in sheep. Full article

This work presents a novel type of soft reconfigurable mobile robot with multimodal locomotion, which is created using a controllable magneto-elastica-reinforced composite elastomer. The rope motor-driven method is employed to modulate magnetics–mechanics coupling effects and enable the magneto-elastica-reinforced elastomer actuator to produce controllable deformations. Furthermore, the 3D-printed magneto-elastica-reinforced elastomer actuators are assembled into several typical robotic patterns: linear configuration, parallel configuration, and triangular configuration. As a proof of concept, a few of the basic locomotive modes are demonstrated including squirming-type crawling at a speed of 1.11 $\mathrm{m}\mathrm{m}/\mathrm{s}$, crawling with turning functions at a speed of 1.11 $\mathrm{m}\mathrm{m}/\mathrm{s}$, and omnidirectional crawling at a speed of 1.25 $\mathrm{m}\mathrm{m}/\mathrm{s}$. Notably, the embedded magnetic balls produce magnetic adhesion on the ferromagnetic surfaces, which enables the soft mobile robot to climb upside-down on ferromagnetic curved surfaces. In the experiment, the inverted ceiling-based inverted crawling speed is 2.17 $\mathrm{m}\mathrm{m}/\mathrm{s}$, and the inverted freeform surface-based inverted crawling speed is 3.40 $\mathrm{m}\mathrm{m}/\mathrm{s}$. As indicated by the experimental results, the proposed robot has the advantages of a simple structure, low cost, reconfigurable multimodal motion ability, and so on, and has potential application in the inspection of high-value assets and operations in confined environments. Full article

Desert plant communities play a vital role in sustaining the stability of arid ecosystems; however, they demonstrate limited resilience to environmental changes. A critical aspect of understanding community assembly mechanisms is determining whether soil texture heterogeneity affects vegetation diversity in arid deserts, especially under conditions of extreme water scarcity and restricted nutrient availability. This study systematically examined the relationships between plant diversity and soil physicochemical properties across four soil texture types—sand, sandy loam, loamy sand, and silty loam—by selecting four representative desert systems in the Hami region of Xinjiang, China. The objective was to elucidate the mechanisms through which soil texture may impact desert plant species diversity. The findings revealed that silty loam exhibited distinct characteristics in comparison to the other three sandy soil types. Despite its higher nutrient content, silty loam demonstrated the lowest vegetation diversity. The Shannon–Wiener index (H′), Simpson dominance index (C), Margalef richness index (D), and Pielou evenness index (Jsw) for silty loam were all lower compared to those for sand, sandy loam, and loamy sand. However, silty loam exhibited higher values in electrical conductivity (EC), urease activity (SUR), and nutrient content, including soil organic matter (SOM), ammonium nitrogen (NH⁴⁺-N), and available potassium (AK), than the other three soil textures. This study underscores the significant regulatory influence of soil texture on plant diversity in arid environments, offering new insights and practical foundations for the conservation and management of desert ecosystems. Full article

To address the issues of bulky structure and complex transmission systems in current transplanters, a compact, electric-driven automatic transplanter was designed. Using pepper plug seedlings as the test subject, this study investigated plug tray dimensions and planting patterns. According to the design requirement that the width of the single-row transplanter must be less than 62.5 cm, a three-dimensional transplanter model was constructed. The transplanter comprises a coaxially installed dual-layer seedling conveying device and a sector-expanding automatic seedling picking and depositing device. The structural dimensions, drive configurations, and driving forces of the transplanter were also determined. Finally, the circuit and pneumatic system were designed, and the transplanter was assembled. Both bench and field tests were conducted to select the optimal working parameters. The test results demonstrated that the seedling picking and depositing mechanism met the required operational efficiency. In static seedling picking and depositing tests, at three transplanting speeds of 120 plants/min, 160 plants/min, and 200 plants/min, the success rates of seedling picking and depositing were 100%, 100%, and 97.5%, respectively. In the field test, at three transplanting speeds of 80 plants/min, 100 plants/min, and 120 plants/min, the transplanting success rates were 94.17%, 90.83%, and 88.33%, respectively. These results illustrate that the compact, electric-driven seedling conveying and picking and depositing devices meet the operational demands of automatic transplanting, providing a reference for the miniaturization and electrification of transplanters. Full article

The design of steel connections presents considerable complexity due to their inherently nonlinear behavior, cost constraints, and the necessity to comply with structural design codes. These factors highlight the need for advanced computational algorithms to identify optimal solutions. In this study, a comprehensive computational framework is presented in which the finite element method (FEM) is integrated with a genetic algorithm (GA) to optimize material usage in bolted steel end-plate joints, while structural safety is ensured based on multiple performance criteria. By incorporating both material and geometric nonlinearities, the mechanical response of the connections is accurately captured. The proposed approach is applied to a representative beam-to-column assembly, with numerical results verified against experimental data. By employing the framework, an optimized layout is obtained, yielding a $10.4\%$ improvement in the overall performance objective compared to the best-performing validated model and a $39.3\%$ reduction in material volume relative to the most efficient feasible alternative. Furthermore, a $53.6\%$ decrease in equivalent plastic strain is achieved compared to the configuration exhibiting the highest level of inelastic deformation. These findings demonstrate that the developed method is capable of enhancing design efficiency and precision, underscoring the potential of advanced computational tools in structural engineering applications. Full article

Poly(ε-caprolactone)-b-polysarcosine (PCL-b-PSar) block copolymers (BCPs) emerge as a promising alternative to conventional poly(ε-caprolactone)-b-poly(ethylene oxide) BCPs for biomedical applications, leveraging superior biocompatibility and biodegradability. In this study, we synthesized two series of PCL-b-PSar BCPs with controlled polymerization degrees (DP of PCL: 45/67; DP of PSar: 28–99) and low polydispersity indexes (Đ ≤ 1.1) and systematically investigated their crystallization-driven self-assembly (CDSA) in alcohol solvents (ethanol, n-butanol, and n-hexanol). It was found that the limited solubility of PSar in alcohols resulted in competition between micellization and crystallization during self-assembly of PCL-b-PSar, and thus coexistence of lamellae and spherical micelles. To overcome this morphological heterogeneity, we developed a modified self-seeding method by employing a two-step crystallization strategy (i.e., T_c1 = 33 °C and T_c2 = 8 °C), achieving conversion of micelles into crystals and yielding uniform self-assembled structures. PCL-b-PSar BCPs with short PSar blocks tended to form well-defined two-dimensional lamellar crystals, while those with long PSar blocks induced formation of hierarchical structures in the PCL₄₅ series and polymer aggregation on crystal surfaces in the PCL₆₇ series. Solvent quality notably influenced the self-assembly pathways of PCL₄₅-b-PSar₂₈. Lamellar crystals were formed in ethanol and n-butanol, but micrometer-scale dendritic aggregates were generated in n-hexanol, primarily due to a significant Hansen solubility parameter mismatch. This study elucidated the CDSA mechanism of PCL-b-PSar in alcohols, enabling precise structural control for biomedical applications. Full article

Background: Chryseobacterium indologenes, an environmental bacterium, is increasingly recognized as an emerging nosocomial pathogen, particularly in Asia, and is often characterized by multidrug resistance. Objectives: This study aimed to investigate the genomic features of clinical C. indologenes isolates from Maharaj Nakorn Chiang Mai Hospital, Thailand, to understand their mechanisms of multidrug resistance, virulence factors, and mobile genetic elements (MGEs). Methods: Twelve C. indologenes isolates were identified, and their antibiotic susceptibility profiles were determined. Whole genome sequencing (WGS) was performed using a hybrid approach combining Illumina short-reads and Oxford Nanopore long-reads to generate complete bacterial genomes. The hybrid assembled genomes were subsequently analyzed to detect antimicrobial resistance (AMR) genes, virulence factors, and MGEs. Results: C. indologenes isolates were primarily recovered from urine samples of hospitalized elderly male patients with underlying conditions. These isolates generally exhibited extensive drug resistance, which was subsequently explored and correlated with genomic determinants. With one exception, CMCI13 showed a lower resistance profile (Multidrug resistance, MDR). Genomic analysis revealed isolates with genome sizes of 4.83–5.00 Mb and GC content of 37.15–37.35%. Genomic characterization identified conserved resistance genes (bla_IND-2, bla_CIA-4, adeF, vanT, and qacG) and various virulence factors. Phylogenetic and pangenome analysis showed 11 isolates clustering closely with Chinese strain 3125, while one isolate (CMCI13) formed a distinct branch. Importantly, each isolate, except CMCI13, harbored a large genomic island (approximately 94–100 kb) carrying significant resistance genes (bla_OXA-347, tetX, aadS, and ermF). The absence of this genomic island in CMCI13 correlated with its less resistant phenotype. No plasmids, integrons, or CRISPR-Cas systems were detected in any isolate. Conclusions: This study highlights the alarming emergence of multidrug-resistant C. indologenes in a hospital setting in Thailand. The genomic insights into specific resistance mechanisms, virulence factors, and potential horizontal gene transfer (HGT) events, particularly the association of a large genomic island with the XDR phenotype, underscore the critical need for continuous genomic surveillance to monitor transmission patterns and develop effective treatment strategies for this emerging pathogen. Full article

Seed germination is a critical phase in the plant lifecycle of Camellia oleifera (oil tea), directly influencing seedling establishment and crop reproduction. In this study, we examined transcriptomic and physiological changes across five defined germination stages (G0–G4), from radicle dormancy to cotyledon emergence. Using RNA sequencing (RNA-seq), we assembled 169,652 unigenes and identified differentially expressed genes (DEGs) at each stage compared to G0, increasing from 1708 in G1 to 10,250 in G4. Functional enrichment analysis revealed upregulation of genes associated with cell wall organization, glucan metabolism, and Photosystem II assembly. Key genes involved in cell wall remodeling, including cellulose synthase (CESA), phenylalanine ammonia-lyase (PAL), 4-coumarate-CoA ligase (4CL), caffeoyl-CoA O-methyltransferase (COMT), and peroxidase (POD) showed progressive activation during germination. A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed dynamic regulation of phenylpropanoid and flavonoid biosynthesis, photosynthesis, carbohydrate metabolism, and hormone signaling pathways. Transcription factors such as indole-3-acetic acid (IAA), ABA-responsive element binding factor (ABF), and basic helix–loop–helix (bHLH) were upregulated, suggesting hormone-mediated regulation of dormancy release and seedling development. Physiologically, cytokinin (CTK) and IAA levels peaked in G4, antioxidant enzyme activities were highest in G2, and starch content increased toward later stages. These findings provide new insights into the molecular mechanisms underlying seed germination in C. oleifera and identify candidate genes relevant to rootstock breeding and nursery propagation. Full article

Climate concerns are driving the automotive industry to adopt advanced manufacturing technologies that aim to improve energy efficiency and reduce vehicle weight. In this context, lightweight structural materials such as aluminium alloys have gained significant attention due to their favorable strength-to-weight ratio. Laser welding plays a crucial role in assembling such materials, offering high flexibility and fast joining capabilities for thin aluminium sheets. However, welding these materials presents specific challenges, particularly in controlling heat input to minimize distortions and ensure consistent weld quality. As a result, numerical simulations based on the Finite Element Method (FEM) are essential for predicting weld-induced phenomena and optimizing process performance. This study investigates welding-induced distortions in laser butt welding of 1.5 mm-thick Al 6061 samples through FEM simulations performed in the SYSWELD 2024.0 environment. The methodology provided by the software is based on the Moving Heat Source (MHS) model, which simulates the physical movement of the heat source and typically requires extensive calibration through destructive metallographic testing. This transient approach enables the detailed prediction of thermal, metallurgical, and mechanical behavior, but it is computationally demanding. To improve efficiency, the Imposed Thermal Cycle (ITC) model is often used. In this technique, a thermal cycle, extracted from an MHS simulation or experimental data, is imposed on predefined subregions of the model, allowing only mechanical behavior to be simulated while reducing computation time. To avoid MHS-based calibration, this work proposes using thermal cycles acquired in-line during welding via infrared thermography as direct input for the ITC model. The method was validated experimentally and numerically, showing good agreement in the prediction of distortions and a significant reduction in workflow time. The distortion values from simulations differ from the real experiment by less than 0.3%. Our method exhibits a slight decrease in performance, resulting in an increase in estimation error of 0.03% compared to classic approaches, but more than 85% saving in computation time. The integration of real process data into the simulation enables a virtual representation of the process, supporting future developments toward Digital Twin applications. Full article

Acoustic tweezers, as advanced micro/nano manipulation tools, play a pivotal role in biomedical engineering, microfluidics, and precision manufacturing. However, piezoelectric-based acoustic tweezers face performance limitations due to multi-physical coupling effects during microfabrication. This study proposes a novel approach using injection molding with embedded electronics (IMEs) technology to fabricate piezoelectric micro-ultrasonic transducers with micron-scale precision, addressing the critical issue of acoustic node displacement caused by thermal–mechanical coupling in injection molding—a problem that impairs wave transmission efficiency and operational stability. To optimize the IME process parameters, a hybrid multi-objective optimization framework integrating NSGA-II and MOPSO is developed, aiming to simultaneously minimize acoustic node displacement, volumetric shrinkage, and residual stress distribution. Key process variables—packing pressure (80–120 MPa), melt temperature (230–280 °C), and packing time (15–30 s)—are analyzed via finite element modeling (FEM) and validated through in situ tie bar elongation measurements. The results show a 27.3% reduction in node displacement amplitude and a 19.6% improvement in wave transmission uniformity compared to conventional methods. This methodology enhances acoustic tweezers’ operational stability and provides a generalizable framework for multi-physics optimization in MEMS manufacturing, laying a foundation for next-generation applications in single-cell manipulation, lab-on-a-chip systems, and nanomaterial assembly. Full article